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Analysis on unit maximum capacity of orthogonal multiple watermarking for multimedia signals in B5G wireless communications

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Digital Communications and Networks 2024年第1期10卷 38-44页

作者： Mianjie Li Senfeng Lai Jiao Wang Zhihong Tian Nadra Guizani Xiaojiang Du Chun Shan School of Electronics and Information Guangdong Polytechnic Normal UniversityGuangzhou510665China Cyberspace Institute of Advanced Technology Guangzhou UniversityGuangzhou510006China Schoolof Electrical Engineering and Computer Science Washington State UniversityPullmanWA99164USA Department of Computer and Information Science Temple UniversityPhiladelphiaPA19122USA

Beyond-5G(B5G)aims to meet the growing demands of mobile traffic and expand the communication *** that intelligent applications to B5G wireless communications will involve security issues regarding user data and operational data,this paper analyzes the maximum capacity of the multi-watermarking method for multimedia signal hiding as a means of alleviating the information security problem of *** multiwatermarking process employs spread transform dither *** the watermarking procedure,Gram-Schmidt orthogonalization is used to obtain the multiple spreading ***,multiple watermarks can be simultaneously embedded into the same position of a multimedia ***,the multiple watermarks can be extracted without affecting one another during the extraction *** analyze the effect of the size of the spreading vector on the unit maximum capacity,and consequently derive the theoretical relationship between the size of the spreading vector and the unit maximum capacity.A number of experiments are conducted to determine the optimal parameter values for maximum robustness on the premise of high capacity and good imperceptibility.

关键词： B5G Multimedia information security Spread transform dither modulation Spreading vector measurement Unit maximum capacity

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Digitally Controllable ASIC for Tri-Color Wireless Photometry

Digitally Controllable ASIC for Tri-Color Wireless Photometr...

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2022 IEEE Biomedical Circuits and Systems Conference, BioCAS 2022

作者： Kirschner, Ravi Marangalou, Amin Hazrati Tsuno, Yusuke Guler, Ulkuhan Worcester Polytechnic Institute Department of Electrical and Computer Engineering WorcesterMA01609 United States Kanazawa University Department of Integrative Neurophysiology Ishikawa920-8640 Japan

ISBN: (数字)9781665469173

ISBN: (纸本)9781665469173

Simultaneously measuring several neurotransmitters will allow researchers to determine how these neurotransmitters influence each other before and during the development of neurological conditions. An example would be the monitoring of acetylcholine - a neurotransmitter that creates the cholinergic pathways responsible for cognitive health - and internal calcium concentration. In this work, we propose a tri-color wireless photometry application specific integrated circuit to measure multiple neurotransmitters simultaneously. The proposed optical excitation channel is fully time-multiplexed and can provide an excitation pulse of between 100 uA and 4 mA with a nominal pulse length of 6.66 Hz, whereas the proposed optical recorder is a fully-differential chopping integrator with three separate channels designed for a 250 μs integration window with a 10 nA current input as well as 2.21 pARMS of input-referred noise integrated from 0.5 Hz to 10 kHz. The presented design is simulated in TSMC 180 nm standard CMOS technology. © 2022 IEEE.

关键词： Application specific integrated circuits

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Improved Cortical Stimulation Efficiency Using 3D Rotating Fields in Transcranial Magnetic Stimulation

Improved Cortical Stimulation Efficiency Using 3D Rotating F...

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2023 IEEE International Symposium on Antennas and Propagation and USNC-URSI Radio Science Meeting, AP-S/URSI 2023

作者： Chinnakkagari, Shashank Manteghi, Majid Virginia Polytechnic Institute and State University Bradley Department of Electrical and Computer Engineering BlacksburgVA United States

ISBN: (纸本)9781665442282

This investigation proposes using 3D rotating fields for coupling the coil with neurons as an alternative to conventional Transcranial Magnetic Stimulation (TMS) techniques. This method requires calculating the field components necessary to rotate the vector field in a two-dimensional plane at a given point of interest Our results indicate that this approach activates neurons in that plane efficiently. In addition, the study demonstrates that selective activation of neurons is possible by restricting the rotation of the vector field plane to a three-dimensional sphere using an external circuit that adjusts the amplitude and phase difference between the field components. computer simulations of human head models with orthogonal coils were used to verify the suggested approach. © 2023 IEEE.

关键词： Neurons

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A Logical Circuit Optimization in Balancing Delay and Energy Consumption 6

A Logical Circuit Optimization in Balancing Delay and Energy...

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6th International Conference on Information Technologies and electrical engineering, ICITEE 2023

作者： Shan, Qihang The Bradley Department of Electrical and Computer Engineering Virginia Polytechnic Institute and State University Blacksburg24061 United States

ISBN: (纸本)9798400708299

The fast-developing chip manufacturing technique and scaling of transistors allow us to fit more transistors on a small chip. The scaling down process, however, is facing a challenge. The smaller transistors are, the more influential quantum channeling and silicon atom size limit become. To improve efficiency, the solution of scaling down is no longer an option. Therefore, to further improve the efficiency of a chip without scaling down transistors, this paper presents a combinational circuit and focuses on an optimization approach where energy consumption is reduced in exchange for increasing delay. By adjusting the size of transistors, energy is saved while maintaining delay to an acceptable range. This approach manages to reduce energy consumption by about 56% while increasing delay by 50%. This paper represents one of many possible approaches that researchers had and has been working on and this tradeoff can benefit some circuit designs depending on the circuit's purpose and hope to bring some insights on further optimization. © 2023 Owner/Author.

关键词： Energy utilization

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Stream-Based Ground Segmentation for Real-Time LiDAR Point Cloud Processing on FPGA

arXiv

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arXiv 2024年

作者： Zhang, Xiao Huang, Zhanhong Antony, Garcia Gonzalez Jachimczyk, Witek Huang, Xinming Department of Electrical and Computer Engineering Worcester Polytechnic Institute MA01609 United States The Computer Vision and Autonomous Vehicles Team The MathWorks MA01760 United States The Department of Electrical and Computer Engineering Worcester Polytechnic Institute MA01609 United States

This paper presents a novel and fast approach for ground plane segmentation in a LiDAR point cloud, specifically optimized for processing speed and hardware efficiency on FPGA hardware platforms. Our approach leverages a channel-based segmentation method with an advanced angular data repair technique and a cross-eight-way flood-fill algorithm. This innovative approach significantly reduces the number of iterations while ensuring the high accuracy of the segmented ground plane, which makes the stream-based hardware implementation possible. To validate the proposed approach, we conducted extensive experiments on the SemanticKITTI dataset. We introduced a bird’s-eye view (BEV) evaluation metric tailored for the area representation of LiDAR segmentation tasks. Our method demonstrated superior performance in terms of BEV areas when compared to the existing approaches. Moreover, we presented an optimized hardware architecture targeted on a Zynq-7000 FPGA, compatible with LiDARs of various channel densities, i.e., 32, 64, and 128 channels. Our FPGA implementation operating at 160 MHz significantly outperforms the traditional computing platforms, which is 12 to 25 times faster than the CPU-based solutions and up to 6 times faster than the GPU-based solution, in addition to the benefit of low power consumption. Copyright © 2024, The Authors. All rights reserved.

关键词： computer graphics equipment

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MGSER-SAM: Memory-Guided Soft Experience Replay with Sharpness-Aware Optimization for Enhanced Continual Learning

MGSER-SAM: Memory-Guided Soft Experience Replay with Sharpne...

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International Joint Conference on Neural Networks (IJCNN)

作者： Xingyu Li Bo Tang Department of Computer Science Tulane University New Orleans United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester United States

ISBN: (数字)9798350359312

ISBN: (纸本)9798350359329

Deep neural networks suffer from the catastrophic forgetting problem in the field of continual learning (CL). To address this challenge, we propose MGSER-SAM, a novel memory replay-based algorithm specifically engineered to enhance the generalization capabilities of CL models. We first intergrate the SAM optimizer, a component designed for optimizing flatness, which seamlessly fits into well-known Experience Replay frameworks such as ER and DER++. Then, MGSER-SAM distinctively addresses the complex challenge of reconciling conflicts in weight perturbation directions between ongoing tasks and previously stored memories, which is underexplored in the SAM optimizer. This is effectively accomplished by the strategic integration of soft logits and the alignment of memory gradient directions, where the regularization terms facilitate the concurrent minimization of various training loss terms integral to the CL process. Through rigorous experimental analysis conducted across multiple benchmarks, MGSER-SAM has demonstrated a consistent ability to outperform existing baselines in all three CL scenarios. Comparing to the representative memory replay-based baselines ER and DER++, MGSER-SAM not only improves the testing accuracy by 24.4% and 17.6% respectively, but also achieves the lowest forgetting on each benchmark.

关键词： Continuing education Training Accuracy Perturbation methods Buildings Artificial neural networks Benchmark testing

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On Neural Collapse in Contrastive Learning with Imbalanced Datasets

On Neural Collapse in Contrastive Learning with Imbalanced D...

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IEEE Workshop on Machine Learning for Signal Processing

作者： Thuan Nguyen Ruijie Jiang Shuchin Aeron Prakash Ishwar D. Richard Brown Department of Engineering Engineering Technology and Surveying East Tennessee State University Department of Electrical and Computer Engineering Tufts University Medford Department of Electrical and Computer Engineering Boston University Boston MA Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester MA

ISBN: (数字)9798350372250

ISBN: (纸本)9798350372267

Neural collapse is a phenomenon in neural networks where all the samples from the same class collapse to their class mean and the class means have a specific geometric structure called Equiangular Tight Frame (ETF). Recent studies have empirically and theoretically confirmed that neural collapse solutions attain a global minimum of Contrastive Learning (CL) losses if the class distribution is uniform (balanced classes). This paper investigates the neural collapse phenomenon in Contrastive Learning for imbalanced datasets. We show that even if the classes are imbalanced, global minima of Contrastive Learning losses include solutions in which all samples from the same class collapse to their class mean. However, the geometric structure of the class means is, in general, different from an ETF. In addition, we show that under certain conditions the optimal geometry of the class means can be found by solving a convex optimization problem. We provide a program based on the CVX package to find these optimal class means.

关键词： Geometry Conferences Neural networks Contrastive learning Machine learning Signal processing Convex functions

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MGSER-SAM: Memory-Guided Soft Experience Replay with Sharpness-Aware Optimization for Enhanced Continual Learning

arXiv

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arXiv 2024年

作者： Li, Xingyu Tang, Bo Department of Computer Science Tulane University New Orleans United States Department of Electrical and Computer Engineering Worcester Polytechnic Institute Worcester United States

关键词： Image classification

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ZCD Circuit Improvement and Novel Signal Processing Method for GaN-Based CRM PWM Converters

ZCD Circuit Improvement and Novel Signal Processing Method f...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Chen, Xingyu Yu, Gibum Li, Qiang Virginia Polytechnic Institute and State University Center for Power Electronics Systems The Bradley Department of Electrical and Computer Engineering BlacksburgVA United States

ISBN: (纸本)9798350376067

This paper introduces a design guidance for zero current detection (ZCD) circuit in Gallium-Nitride (GaN) device based critical conduction mode (CRM) pulse-width-modulation (PWM) converters to reduce the sensing delay, avoid false trigger and prevent trigger missing. A ZCD signal processing logic is also proposed for CRM PWM converters to limit the maximum switching frequency while keeping a simple closed loop control structure. The proposed ZCD circuit design and ZCD signal processing method are verified in the simulation and on a GaN based CRM buck converter. © 2024 IEEE.

关键词： Pulse width modulation

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Symmetric Series-Capacitor Buck in 48V-to-12V Regulated Conversion for High-Performance Server Boards

Symmetric Series-Capacitor Buck in 48V-to-12V Regulated Conv...

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2024 IEEE Energy Conversion Congress and Exposition, ECCE 2024

作者： Xu, Xinmiao Li, Qiang Virginia Polytechnic Institute and State University Center for Power Electronics Systems Department of Electrical and Computer Engineering BlacksburgVA24061 United States

ISBN: (纸本)9798350376067

This paper presents an extended-conversion-ratio modulation for a two-phase symmetric series-capacitor buck (SSCB) converter. With the proposed scheme, highly efficient and regulated 48V-to-12V conversion can be realized with the SSCB topology. A versatile regulated first stage streamlines power delivery architectures for server boards in data centers, because regulated 12-V buses not only serve loads requiring well-controlled 12-V input but also simplify design and optimization of a 12V-to-1V second stage for processors. Based on this idea, a highly efficient and regulated power architecture is proposed for 48-V server boards. A prototype is built with gallium nitride (GaN) transistors and minimal high-frequency loop inductance, operating with a relatively wide input voltage range from 40 V to 60 V and generating a regulated 12-V output. In 48V-to-12V regulated conversion, the GaN-based prototype achieves 98.88% peak efficiency, 98.11% full-load efficiency (including gating loss) and 787 W/inch2 power density with 80-A output current, which is beyond the performance of state-of-the-art commercially available solutions. © 2024 IEEE.

关键词： Gallium nitride

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